BackgroundThere are three main dietary groups in mammals: carnivores, omnivores, and herbivores. Currently, there is limited comparative genomics insight into the evolution of dietary specializations in mammals. Due to recent advances in sequencing technologies, we were able to perform in-depth whole genome analyses of representatives of these three dietary groups.ResultsWe investigated the evolution of carnivory by comparing 18 representative genomes from across Mammalia with carnivorous, omnivorous, and herbivorous dietary specializations, focusing on Felidae (domestic cat, tiger, lion, cheetah, and leopard), Hominidae, and Bovidae genomes. We generated a new high-quality leopard genome assembly, as well as two wild Amur leopard whole genomes. In addition to a clear contraction in gene families for starch and sucrose metabolism, the carnivore genomes showed evidence of shared evolutionary adaptations in genes associated with diet, muscle strength, agility, and other traits responsible for successful hunting and meat consumption. Additionally, an analysis of highly conserved regions at the family level revealed molecular signatures of dietary adaptation in each of Felidae, Hominidae, and Bovidae. However, unlike carnivores, omnivores and herbivores showed fewer shared adaptive signatures, indicating that carnivores are under strong selective pressure related to diet. Finally, felids showed recent reductions in genetic diversity associated with decreased population sizes, which may be due to the inflexible nature of their strict diet, highlighting their vulnerability and critical conservation status.ConclusionsOur study provides a large-scale family level comparative genomic analysis to address genomic changes associated with dietary specialization. Our genomic analyses also provide useful resources for diet-related genetic and health research.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1071-4) contains supplementary material, which is available to authorized users.

We present the initial phase of the Korean Genome Project (Korea1K), including 1094 whole genomes (sequenced at an average depth of 31×), along with data of 79 quantitative clinical traits. We identified 39 million single-nucleotide variants and indels of which half were singleton or doubleton and detected Korean-specific patterns based on several types of genomic variations. A genome-wide association study illustrated the power of whole-genome sequences for analyzing clinical traits, identifying nine more significant candidate alleles than previously reported from the same linkage disequilibrium blocks. Also, Korea1K, as a reference, showed better imputation accuracy for Koreans than the 1KGP panel. As proof of utility, germline variants in cancer samples could be filtered out more effectively when the Korea1K variome was used as a panel of normals compared to non-Korean variome sets. Overall, this study shows that Korea1K can be a useful genotypic and phenotypic resource for clinical and ethnogenetic studies.

Early Neolithic (~7700-year-old) genetic data from the Russian Far East implies a high level of genetic continuity in this region.

The endangered whale shark (Rhincodon typus) is the largest fish on Earth and a long-lived member of the ancient Elasmobranchii clade. To characterize the relationship between genome features and biological traits, we sequenced and assembled the genome of the whale shark and compared its genomic and physiological features to those of 83 animals and yeast. We examined the scaling relationships between body size, temperature, metabolic rates, and genomic features and found both general correlations across the animal kingdom and features specific to the whale shark genome. Among animals, increased lifespan is positively correlated to body size and metabolic rate. Several genomic traits also significantly correlated with body size, including intron and gene length. Our large-scale comparative genomic analysis uncovered general features of metazoan genome architecture: Guanine and cytosine (GC) content and codon adaptation index are negatively correlated, and neural connectivity genes are longer than average genes in most genomes. Focusing on the whale shark genome, we identified multiple features that significantly correlate with lifespan. Among these were very long gene length, due to introns being highly enriched in repetitive elements such as CR1-like long interspersed nuclear elements, and considerably longer neural genes of several types, including connectivity, activity, and neurodegeneration genes. The whale shark genome also has the second slowest evolutionary rate observed in vertebrates to date. Our comparative genomics approach uncovered multiple genetic features associated with body size, metabolic rate, and lifespan and showed that the whale shark is a promising model for studies of neural architecture and lifespan.

More than 300 million people worldwide experience depression; annually, ~800,000 people die by suicide. Unfortunately, conventional interview-based diagnosis is insufficient to accurately predict a psychiatric status. We developed machine learning models to predict depression and suicide risk using blood methylome and transcriptome data from 56 suicide attempters (SAs), 39 patients with major depressive disorder (MDD), and 87 healthy controls. Our random forest classifiers showed accuracies of 92.6% in distinguishing SAs from MDD patients, 87.3% in distinguishing MDD patients from controls, and 86.7% in distinguishing SAs from controls. We also developed regression models for predicting psychiatric scales with R2 values of 0.961 and 0.943 for Hamilton Rating Scale for Depression–17 and Scale for Suicide Ideation, respectively. Multi-omics data were used to construct psychiatric status prediction models for improved mental health treatment.